Application of Radial Basis Function Neural Network to Support Concept Evaluation

Abstract:

In order to solve the problem that how to evaluate the complex system support concept, an evaluation method based on Radial Basis Function (RBF) neural network model was presented. Through researching the support system overall design characteristics and elements of support, on this basis, evaluation parameters of support concept were abstracted. Support concept evaluation model based on RBF was established and a mature and stable RBF neural network was trained to calculate the comprehensive evaluation value for support concept. Finally, the further demonstration and verification of the method are given through specific case application and compared with the result for evaluation results of data envelopment analysis (DEA) model.

• Periodical: Advanced Materials Research (Volumes 472-475)
• Pages: 1926-1931
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.472-475.1926
• Online since: February 2012
• Authors: Qing Wei Yang, Nai Chao Wang, Ma Lin
• Keywords: Evaluation, Evaluation Criteria, Radial Basis Function Neural Network (RBFNN), Support Concept

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